Many image enhancement processes use image comparisons, wherein two or more images of the same object are compared. Examples of comparison techniques are subtraction, merger, and addition. The image subtraction process is especially used where changing or changed characteristics are of interest, such as in certain diagnostic medical imaging i.e. digital fluorography (DF).
The subtraction method presently in vogue is temporal subtraction and is generally accomplished either by "mask" or "TID" methods. In the "mask" method a selected prior image is subtracted from subsequent images. In the "TID" method, selected ones of a series of prior images are subtracted from selected ones of a series of subsequent images. In both cases it is apparent that the images used for subtraction must be in registration to provide artifact free results (registration means that the same features are in the same positions in both images). In DF misregistration occurs mainly because of patient motion.
In digital fluorography e.g., the misregistration problem is especially aggravated by the subject's movement between the "mask" imaging and the subsequent imaging. For example, the imaging sequence in DF normally takes approximately 15 seconds. While the subjects are instructed to hold their breath and not to swallow during this time period; nonetheless, they often do with resultant motion and misregistration.
Prior to the invention of the above noted patent application the methods for correcting for misregistration, most commonly used either edge recognition and comparison or point recognition and comparison to determine the amount of misregistration. Edges are relatively easy to recognize using differences or derivatives of some sort. Thus it is feasible to measure the motion i.e., the distance traversed by a recognized edge- especially if the direction of motion is in a direction of motion normal to the edge. However motions parallel to the edges are difficult to discern.
Points are relatively difficult to recognize. The maximum or minimum points are located in regions of small average gradients. Local "noise" also tends to play havoc with the linearity of the system and therefore move the measured point from its actual location to an apparent location. Low pass filters can be used to reduce the noise level but such filters also reduce the derivatives and therefore add an uncertainty to the actual location of the point.
"Global" points, for example, the center of gravity ("COG") of the data in some region of interest ("ROI") depend on the definition of the ROI and therefore have not been sufficiently definitive of the points for use in misregistration correction. For example, if the data is a step function with the step at point X0 in the "mask" and at a point X1 in the image; an ROI that includes both points yields a shift in COG of (X1-X0)/2 when the shift of the point is really (X1-X0). To correctly define the shift a larger ROI that includes the opposite step is required. Such a large ROI will encompass complete organs and therefore data that has really changed, e.g. through inflow of contrast material and such data can raise difficulties when used for misregistration correction. The correction for misregistration used prior to the noted invention were therefore often incorrect and/or non-effective.
The above noted invention provides means and methods for vectorally determining the image shift between images that are compared and/or subtracted one from the other. According to a broad aspect of that invention a method was provided for determining the motion of the subject that has occurred between first and second temporally separated images of the said subject. The method comprises a first step of selecting an ROI on each of the temporally seperated images wherein the ROI encompasses an image characteristic caused by the actual motion of the subject. The ROI should not include non-repeatable or secondary characteristics. A point is selected in each of the images representing the position of the characteristic encompassed in the ROI. An example of points used in the above mentioned patent application was the centers of gravity (COG) of the the squared amplitudes of the gradients of the gray level densities. The next step is finding the vector between the representative points. The noted inventive method unfortunately has a characteristic weakness. It errs in locating the points such as the COG's when there are secondary characteristics located proximate to the boundaries of the selected ROI's. Inherent shifts often incorporate the secondary features in an ROI in one image while excluding it in the other image. Consequently the points selected for determining the vectors are then in error.
Thus, there is a need for means and methods for correcting artifacts generated by motion of a subject being imaged even where the images have secondary characteristics located proximate to the boundaries of the ROI in the image.
Accordingly, there is provided a method of correcting artifacts generated by motion of a subject being imaged occurring between temporally seperated images, said method comprising the steps of:
obtaining a vector value representative of the motion of the said subject, PA1 said last named step including the steps of: PA1 selecting an ROI about an imaged part such as a bone having a characteristic in the image wherein changes in the intensity per pixel are due largely to the said motion, said imaged part displaying a primary characteristic and a possible secondary characteristic wherein changes in the intensity per pixel are due largely to the said motion and wherein the amplitude of the secondary characteristic is less than the amplitude of the primary characteristic, PA1 determining the representative points (e.g. COG's) based on the primary characteristic in said ROI on each of said images, PA1 reducing the effects of the secondary characteristics in the step of determining the representative points of the primary characteristics, and PA1 determining the vector extending between representative points in each of said images to define the amount and direction of the subject motion.
A feature of the invention includes selecting the ROI's to reduce the effects of the secondary characteristic.
A further feature of the invention includes reducing the secondary characteristics to reduce the effects of the secondary characteristics in determining the representative points.
Yet another feature of the invention includes reducing the effects of the secondary characteristics on the representative points by setting the ROI's after determining the maximum point of the primary characteristic and defining the ROI as encompassing the primary characteristic at a determined percentage of the maximum.
Yet another feature of the invention comprises reducing the secondary characteristics by setting all pixel values below a threshold value to zero in determining the representative points.
Still another method for reducing the effects of secondary characteristics on the representative points comprises using a ramp function multiplier on ROI boundary gradient values.